Supercurrent diode effect and magnetochiral anisotropy in few-layer NbSe2_2

Nonreciprocal transport refers to charge transfer processes that are sensitive to the bias polarity. Until recently, nonreciprocal transport was studied only in dissipative systems, where the nonreciprocal quantity is the resistance. Recent experiments have, however, demonstrated nonreciprocal supercurrent leading to the observation of a supercurrent diode effect in Rashba superconductors, opening the vision of dissipationless electronics. Here we report on a supercurrent diode effect in NbSe$_2$ constrictions obtained by patterning NbSe$_2$ flakes with both even and odd layer number. The observed rectification is driven by valley-Zeeman spin-orbit interaction. We demonstrate a rectification efficiency as large as 60%, considerably larger than the efficiency of devices based on Rashba superconductors. In agreement with recent theory for superconducting transition metal dichalcogenides, we show that the effect is driven by an out-of-plane magnetic field component. Remarkably, we find that the effect becomes field-asymmetric in the presence of an additional in-plane field component transverse to the current direction. Supercurrent diodes offer a further degree of freedom in designing superconducting quantum electronics with the high degree of integrability offered by van der Waals materials.Comment: 18 pages, 12 figure

Toward Global Soil Moisture Monitoring With Sentinel-1: Harnessing Assets and Overcoming Obstacles

The final authenticated publication is available at https://doi.org/10.1109/TGRS.2018.2858004.Soil moisture is a key environmental variable, important to, e.g., farmers, meteorologists, and disaster management units. Here, we present a method to retrieve surface soil moisture (SSM) from the Sentinel-1 (S-1) satellites, which carry C-band Synthetic Aperture Radar (CSAR) sensors that provide the richest freely available SAR data source so far, unprecedented in accuracy and coverage. Our SSM retrieval method, adapting well-established change detection algorithms, builds the first globally deployable soil moisture observation data set with 1-km resolution. This paper provides an algorithm formulation to be operated in data cube architectures and high-performance computing environments. It includes the novel dynamic Gaussian upscaling method for spatial upscaling of SAR imagery, harnessing its field-scale information and successfully mitigating effects from the SAR's high signal complexity. Also, a new regression-based approach for estimating the radar slope is defined, coping with Sentinel-1's inhomogeneity in spatial coverage. We employ the S-1 SSM algorithm on a 3-year S-1 data cube over Italy, obtaining a consistent set of model parameters and product masks, unperturbed by coverage discontinuities. An evaluation of therefrom generated S-1 SSM data, involving a 1-km soil water balance model over Umbria, yields high agreement over plains and agricultural areas, with low agreement over forests and strong topography. While positive biases during the growing season are detected, the excellent capability to capture small-scale soil moisture changes as from rainfall or irrigation is evident. The S-1 SSM is currently in preparation toward operational product dissemination in the Copernicus Global Land Service.5205392

Clarifications on the "Comparison Between SMOS, VUA, ASCAT, and ECMWF Soil Moisture Products Over Four Watersheds in U.S."

In a recent paper, Leroux et al. compared three satellite soil moisture data sets (SMOS, AMSR-E, and ASCAT) and ECMWF forecast soil moisture data to in situ measurements over four watersheds located in the United States. Their conclusions stated that SMOS soil moisture retrievals represent "an improvement [in RMSE] by a factor of 2-3 compared with the other products" and that the ASCAT soil moisture data are "very noisy and unstable." In this clarification, the analysis of Leroux et al. is repeated using a newer version of the ASCAT data and additional metrics are provided. It is shown that the ASCAT retrievals are skillful, although they show some unexpected behavior during summer for two of the watersheds. It is also noted that the improvement of SMOS by a factor of 2-3 mentioned by Leroux et al. is driven by differences in bias and only applies relative to AMSR-E and the ECWMF data in the now obsolete version investigated by Leroux et al

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

Validation and improvement of the Freeze/Thaw detection algorithm from ASCAT data

Zsfassung in dt. SpracheThe Freeze/Thaw state of the surface has wide reaching consequences for numerous processes in nature. It is coupled to the surface energy budget, hydrological activity which starts when melting begins, vegetation growing season dynamics,the terrestrial carbon budget and also the remote sensing retrieval of soil moisture, which is not valid if the soil is frozen. Mainly because of the last reason, the Institute for Photogrammetry and Remote Sensing at the Technical University of Vienna has recently developed an empirical threshold analysis algorithm for the detection of frozen surface states using only the ASCAT data. Previously the ASCAT Scatterometer on-board the MetOp-A satellite provided soil moisture measurements but depended on external probabilistic data for flagging measurements taken over frozen ground. The algorithm uses the distribution of normalized backscatter measurements (sigma 40) over temperature to find parameters that characterize the behaviour of backscatter when freezing occurs. Based on these parameters a decision tree based approach is used for freeze/thaw detection. Th is work presents a first validation of the resulting freeze/thaw product using different global and regional temperature datasets ranging from model data (ERA-INTERIM, GLDAS-NOAH) and in-situ measurements (WMO-METEO stations, GTN-P borehole data) to satellite derived land surface temperature (MODIS-LST,AATSR-LST). The validation shows good agreement between the extracted frozen/unfrozen -flag and the temperature data but also the need for improvement in certain situations. The shortcomings of the algorithm are found to be ambiguities in the backscatter/temperature relationship as well as systematic problems in some areas. As a last step it was tried to simplify, and make the algorithm more robust through the use of ancillary data that eliminates the need to account for numerous possible cases of backscatter in summer and winter and focuses on the critical times in spring and autumn when most freeze/thaw events take place. The results of these slight modications were then validated using the same datasets and the results were improved in most cases.Der Frostzustand der Erdoberfläche hat weitreichende Konsequenzen für eine vielzahl von Vorgängen in der Natur. Der Bodenenergiehaushalt, der Wasserzyklus, die Wachstumszeiten der Pflanzen, der Kohlenstoffhaushalt der Erde, und auch die Messung der Bodenfeuchte mit Fernerkundungstechnologien, welche bei gefrorenem Boden nicht möglich ist, sind stark vom Frostzustand abhängig. Am Institut für Photogrammetrie und Fernerkundung and der TU Wien wurde ein empirischer, auf Schwellenwerten basierender Algorithmus entwickelt, welcher es ermöglicht den Frostzustand nur mithilfe von ASCAT Daten festzustellen. Vor dieser Entwicklung war die vom ASCAT Scatterometer gemessene Bodenfeuchte von externen Wahrscheinichkeiten für gefrorenen Boden abhänging, um Messwerte zu erkennen die über selbigem gemacht wurden.Der Algorithmus verwendet die Verteilung von normalisierter Rückstreuung (sigma 40) über Temperaturmesswerten um daraus Parameter abzuleiten welche das Verhalten der Rückstreuung beim gefrieren des Bodens beschreiben. Basierend auf diesen Parametern führen mehrere Entscheidungsbäume zu einer Aussage über den Frostzustand. Im Zuge dieser Arbeit wurde eine erste Valdierung des resultierenden Produktes mit unterschiedlichen globalen und regionalen Temperaturdatensätzen vorgenommen. Dabei wurden sowohl Klimamodelle (ERA-INTERIM, GLDAS-NOAH) als auch in situ Messwerte (WMO-METEO Stationen, GTN-P Bohrlochdaten) und von Satelliten gemessene Bodentemperaturdaten (MODIS-LST,AATSR-LST) verwendet. Die Validierung zeigt gute Übereinstimmungen zwischen dem abgeleiteten Frostzustand und den verschiedenen Datensätzen, aber auch die Notwendigkeit von Verbesserungen in bestimmten Situationen.Die Probleme des Algorithmus treten hauptsächlich dann auf wenn der Zusammenhang zwischen Rückstreuung und Temperatur nicht eindeutig gegeben ist, es kommen aber in machen Gebieten noch systematische Fehler hinzu. Als letzter Schritt wurde versucht die Entscheidungsbäume zu vereinfachen und die Robustheit des Algorithmus zu verbessern indem durch externe Datensätze die zu berücksichtigenden Kombinationen von Rückstreuung und Temperatur, minimiert werden. Dadurch kann sich der Algorithmus auf die für den Frostzustand wichtige Zeit in Frühling und Herbst konzentrieren. Die Ergebnisse dieser Änderungen wurden ebenfalls validiert und bedeuten in den meisten Fällen eine Verbesserung.7

smap_io v0.2

Add metadata from netCDF file to returned image. Add option to return data as 1D arrays. Add image to time series conversion and time series reading interface

TUW-GEO/ecmwf_models v0.3

Fix help text in ecmwf_repurpose command line program. Fix reading of metadata for variables that do not have 'levels' Fix wrong import when trying to read the reformatted time series data

ESA DUE Permafrost: Evaluation of remote sensing derived products using ground data from the Global Terrestrial Network of Permafrost (GTN-P)

The task of the ESA DUE Permafrost project is to build up an Earth observation service for high-latitudinal permafrost applications with extensive involvement of the permafrost research community. The DUE Permafrost products derived from remote sensing are land surface temperature (LST), surface soil moisture (SSM), surface frozen and thawed state (freeze/ thaw), terrain, land cover, and surface waters. Weekly and monthly averages for most of the DUE Permafrost products will be made available for the years 2007-2010. The DUE Permafrost products are provided for the circumpolar permafrost area (north of 55°N) with 25 km spatial resolution. In addition, regional products with higher spatial resolution (300-1000 m/ pixel) were developed for five case study regions. These regions are: (1) the Laptev Sea and Eastern Siberian Sea Region (RU, continuous very cold permafrost/ tundra), (2) the Yakutsk Region (RU, continuous cold permafrost/ taiga), (3) the Western Siberian transect including Yamal Peninsula and Ob Region (RU, continuous to discontinuous/ taiga-tundra), (4) the Alaska Highway Transect (US, continuous to discontinuous/ taiga-tundra), and (5) the Mackenzie Delta and Valley Transect (CA, continuous to discontinuous/ taiga-tundra). The challenge of the programme is to adapt remote sensing products that are well established and tested in agricultural low and mid-latitudinal areas for highly heterogeneous taiga/ tundra permafrost landscapes in arctic regions. Ground data is essential for the evaluation of DUE Permafrost products and is provided by user groups and global networks. A major part of the DUE Permafrost core user group is contributing to GTN-P, the Global Terrestrial Network of Permafrost. Its main programmes, the Circumpolar Active Layer Monitoring (CALM) and the Thermal State of Permafrost (TSP) have been thoroughly overhauled during the last International Polar Year (2007-2008). Their spatial coverage has been extended to provide a true circumpolar network. Ground data ranges from active layer- and snow depths, to air-, ground-, and borehole temperature data as well as soil moisture measurements and the description of landform and vegetation. The GTN-P sites, with their position in different permafrost zones in the DUE Permafrost case study regions, are highly suitable for the evaluation of DUE Permafrost remote sensing products. Air and surface temperatures with high-temporal resolution are available for three GTN-P sites in Siberia and compared to LST products. Daily average GTN-P borehole- and air temperature data for 22 sites in Alaska and 6 sites in Western Siberia were used to validate surface frozen and thawed state. The preliminary results are promising. In addition, landform and vegetation descriptions of circumpolar GTN-P sites are used for the evaluation of global ‘landcover’ remote-sensing datasets like GlobeCover, Landcover2000 and EcoClimap – global datasets used as input for climate modeling

TUW-GEO/ascat: v0.7

Fix bugs in BUFR reading with newer numpy versions